Literature DB >> 18982611

Estimation of ground-glass opacity measurement in CT lung images.

Yuanjie Zheng1, Chandra Kambhamettu, Thomas Bauer, Karl Steiner.   

Abstract

We propose to measure quantitatively the opacity property of each pixel in a ground-glass opacity tumor from CT images. Our method results in an opacity map in which each pixel takes opacity value of [0-1]. Given a CT image, our method accomplishes the estimation by constructing a graph Laplacian matrix and solving a linear equations system, with assistance from some manually drawn scribbles for which the opacity values are easy to determine manually. Our method resists noise and is capable of eliminating the negative influence of vessels and other lung parenchyma. Experiments on 40 selected CT slices of 11 patients demonstrate the effectiveness of this technique. The opacity map produced by our method is invaluable in practice. From this map, many features can be extracted to describe the spatial distribution pattern of opacity and used in a computer-aided diagnosis system.

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Year:  2008        PMID: 18982611     DOI: 10.1007/978-3-540-85990-1_29

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  2 in total

1.  Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

Authors:  Ayman El-Baz; Garth M Beache; Georgy Gimel'farb; Kenji Suzuki; Kazunori Okada; Ahmed Elnakib; Ahmed Soliman; Behnoush Abdollahi
Journal:  Int J Biomed Imaging       Date:  2013-01-29

2.  Automatic Graph Cut Segmentation of Lesions in CT Using Mean Shift Superpixels.

Authors:  Xujiong Ye; Gareth Beddoe; Greg Slabaugh
Journal:  Int J Biomed Imaging       Date:  2010-10-28
  2 in total

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